• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.949-964
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• 2021

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.354-368
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• 2020

Accurate and versatile image data-sets are essential for fashion AI research and AI-based fashion businesses based on a systematic attribute classification system. This study constructs a color and texture attribute hierarchical classification system by collecting fashion item images and analyzing the metadata of fashion items described by consumers. Essential dimensions to explain color and texture attributes were extracted; in addition, attribute values for each dimension were constructed based on metadata and previous studies. This hierarchical classification system satisfies consistency, exclusiveness, inclusiveness, and flexibility. The image tagging to confirm the usefulness of the proposed classification system indicated that the contents of attributes of the same image differ depending on the annotator that require a clear standard for distinguishing differences between the properties. This classification system will improve the reliability of the training data for machine learning, by providing standardized criteria for tasks such as tagging and annotating of fashion items.

• Journal of Korean Library and Information Science Society
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• v.43 no.3
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• pp.101-120
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• 2012

This study investigated general problems concerning the clothing and textiles field in the KDC 5th edition based comparative analysis academic characteristics and classification system, and suggested on some ideas for the improvements of them. Results of the study is summarized as follows. First, the classification system of the clothing and textiles field is generally divided by costume, dyeing engineering, leather & fur processing, textiles and textile industries, manufacturing clothes, management of clothing, and textile arts. Second, I proposed improvements based on analyzing problems of KDC 5th to the clothing and textiles field from the collection database at the National Library of Korea. Third, basically improvements of KDC system was based on the knowledge of the clothing and textiles field. I tried to maintain as the KDC existing classification system was to retain as much as possible, and to move between items was minimal.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.6
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• pp.857-865
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• 1995

The main purposes of this study were to find out the new classification system of the clothing evaluative criteria(CEC), 3nd to clear up the relationshiops of new classification system and the existing classification systems. For this purpose, the existing literatures related with the CEC(the classification system, and the variables) were investigated. The results of the study were as follows: 1. The existing classification systems were 'the intrinsic. non-intrinsic classification', 'the level classification', 'the purchase process classification' The new classification system of the CEC is based on 'the view-point of subjets'. The system was divided into the point of clothing itself, the wearer, the other, the wearing situation. The wearer's point of view is divided into the point of the value, and the physical characteristics of wearer 2. The image was included as the concept of the CEC, and the image classification could be suggested. 3. The relationships of the classification systems were as follows: $\circled1$ The intrinsic. non-intrinsic classification system included the level classification, the view-point classification, the image classification, and the buying process classificstion. $\circled2$ The level classification, the view.point classification, and the image classification were linked mutually, but the buying process classification is seperated from these classifications.

• Journal of the Korean Society of Clothing and Textiles
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• v.13 no.3 s.31
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• pp.223-241
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• 1989

As a preliminary work for the clothing conformity study, Its theoretical backgrounds were reviewed. In the view of convertibility into clothing conformity, two prevailing conformity types were studied. One is normative-social influence and informational-social influence classified by Deutsch and Gerald. And the other is Kelman's classification which includes compliance, identification and internalization. Reference group, as an object of conformity, was studied. In addition to Engel and Blackwell' s and Assael's classification, the reference groups which were revealed in the studies of consumer behavior and clothing behavior were reviewed. The factors were reviewed which influence conformity and clothing conformity. They were product factor, group factor, situational factor and individual factor.

• Proceedings of the Costume Culture Conference
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• 2005.10a
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• pp.117-120
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• 2005

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.4
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• pp.529-538
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• 1993

This study was intended to identify the hierarchy of clothing images, which is expected to be helpful in style classification and product positioning. A questionnaire consisted of 110 words expressing clothing images was developed, and eight clothing photographs were selected as stimuli. 289 female subjects aged between 22 to 37 responded to two of the eight photographs during September, 1991. 110 words were reduced to 62 words based on their independence before conducting factor analysis to identify the constructing factors of clothing images. Nine words with negative connotations were eliminated, because they are not sought in product development. To explain the hierarchy of clothing images, cluster analysis was applied. To observe the association of 53 words, dendrogram was introduced, and to interpret the result, eleven sub clusters were determined. This 11 clusters were continuously combined according to their similarities, until they integrated into one 'clothing image'. Two major division of image clusters were 'graceful and feminine image', and 'mannish and simple image'.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.3
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• pp.385-392
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• 2010

The breast types of middle-aged women of 80A (formerly 80B) size were classified through a 3D scanned nude body. Thirty seven measurements including the radius of curvature, surface area, volume, surface length, and breast displacements were used as input variables. We extracted five main factors through the factor analysis of the measurements and classified 36 subjects into 3 clusters through the cluster analysis. As a result of the factor analysis, the size of the breast, breast sag, the curvature of the inner and the outer breast curve, the width of the breast, and the nipple direction were found as the main factors. For the results of the classification of breast types, Cluster 1 was characterized by narrow breast width and unsymmetrical under the breast curve, whereas Cluster 2 was a wide and sagged shape. Cluster 3 was classified into big breast volume and symmetrical under-breast curve. The results are useful to the product development of high quality brassieres which reflect the 3D characteristics of breast types of middle-aged women.

• The Research Journal of the Costume Culture
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• v.7 no.3
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• pp.108-120
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• 1999

This research analyzes characterization and classification of body types for the Chinese women with body measurement values. The measurement has gauged in 1999 in Beijing Institute of Clothing Technology in China. 100 women of the Chinese college women aged 17 and 24 in China were measured for this research. In the results of frequency analysis, the tall of Chinese women were 158.37㎝ and also has less than 150㎝ high, and has thick under bust circumference, and has a group of more than 18㎝ for width of nipple. In the results of factor analysis, Factor 1 represented the degree of abesity, while factor 2 indicated the stature and the arm length. The body types are classified into five types by cluster analysis. The stature and weight varied according to types, leading to a classification focusing on the body size determined by stature and weight factors.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.2
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• pp.287-304
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• 2016

This study examines the influence of product classification standards and structure on user perception as well as their attitude towards online shopping sites. The causal relationships of variables are also examined. The analysis was based on an online survey with 247 responses. Four types of internet shopping sites were developed and used as a stimulus. The results of the mean comparison analysis indicated that perceived variety, information overload, perceived shopping value and attitude towards the site varies significantly with product classification standards and structure. There was also of a marginally significant interaction between the classification standard and structure on perceived variety and information overload. The causal relationship analysis revealed that perceived variety positively influenced hedonic and utilitarian shopping value. However, information overload had a negative effect on hedonic and utilitarian shopping value. Both the hedonic and utilitarian shopping value positively influenced attitudes towards the sites. This study demonstrates that classification method influences customer perception and attitude. It offers interesting insights on a product classification method as a strategic tool for online shopping.